An investigation on performance of Significance Analysis of Microarray (SAM) for the comparisons of several treatments with one control in the presence of small-variance genes.
One of multiple testing problems in drug finding experiments is the comparison of several treatments with one control. In this paper we discuss a particular situation of such an experiment, i.e., a microarray setting, where the many-to-one comparisons need to be addressed for thousands of genes simultaneously. For a gene-specific analysis, Dunnett's single step procedure is considered within gene tests, while the FDR controlling procedures such as Significance Analysis of Microarrays (SAM) and Benjamini and Hochberg (BH) False Discovery Rate (FDR) adjustment are applied to control the error rate across genes. The method is applied to a microarray experiment with four treatment groups (three microarrays in each group) and 16,998 genes. Simulation studies are conducted to investigate the performance of the SAM method and the BH-FDR procedure with regard to controlling the FDR, and to investigate the effect of small-variance genes on the FDR in the SAM procedure.
Lin
D
D
Center for Statistics, Hasselt University, Agoralaan-Building D, 3590 Diepenbeek, Belgium. dan.lin@ uhasselt.be
Shkedy
Z
Z
Burzykowski
T
T
Ion
R
R
Göhlmann
H W H
HW
Bondt
A De
AD
Perer
T
T
Geerts
T
T
Van den Wyngaert
I
I
Bijnens
L
L
D001699:Biometry / Q000379:methods*; D055808:Drug Discovery / Q000706:statistics & numerical data; D020869:Gene Expression Profiling / Q000706:statistics & numerical data; D006801:Humans; D016014:Linear Models; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis / Q000706:statistics & numerical data*